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Modern Methods of Clinical Investigation (1990)

Chapter: 3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection

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Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
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Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
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Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
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Page 25
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 26
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 27
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 28
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 29
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 30
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
×
Page 31
Suggested Citation:"3. Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Experimental Data Collection." Institute of Medicine. 1990. Modern Methods of Clinical Investigation. Washington, DC: The National Academies Press. doi: 10.17226/1550.
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Page 32

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3 Advances in Health Status Measurement: The Potential to Improve Experimental and Non-Exper~mental Data Collection MARILYN BERGNER Advances in health status measurement have given us a choice of reliable and valid measures to use in clinical trials of drugs and devices. To use them, however, investigators may have to revise the design of trials and their data col- lection methods. The primary objective of this paper is to familiarize the reader with current health status measures. The secondary objectives are almost equal- ly important. They are to examine the way clinical trials are conducted, to dis- tinguish between quality of life and health status measures, to suggest modifica- tions necessary to incorporate health status measures into clinical trials, and to discuss four problems that are often cited as barriers to the use of health status measures. THE CONDUCT OF CLINICAL TRIALS Phase II or Phase III clinical trials of new drugs and medical devices are gen- erally conducted in the following fashion. They generally take place in many medical centers throughout the country and sometimes even in several coun- tries. The incentive for the participation of these centers or of physicians is the fee received for patients enrolled in the trial. Usually the fee is meant to cover the cost of data collection, including personnel and additional testing. Each center hires staff or assigns existing staff to collect the needed information. Since the health professionals participating in the trial are those providing clini- cal care, they usually are principally expert in clinical medicine rather than eval- uative research. The design of trials and data collection forms is done by the coordinating center—usually a department of the firm running the study. The format of these 23

24 MARILYN BERGNER data collection instruments is often a compromise between completeness, ease of recording by the primary data collector, ease of conversion to computer-read- able form, and ease of analysis. The ones I have seen tend to be closely packed with questions, with limited space for answers. Some questions are straightfor- ward: What is the patient's blood pressure? But some of them require judg- ment: What size is the mass? Is the tumor shrinking? Has the patient had any side effects? There are few or no guidelines about the kind of information that must be provided to answer these questions. The data collected in these trials refer only to the patients enrolled in the study. No information is obtained about patients who were considered for enrollment but, for one reason or another, were not approached by the physician or staff members. Furthermore, patients often drop out without anyone inquiring why they left. The dropout is sometimes recorded on the chart or form but, more often than not, the only source of that information is the physician. Finally, these studies generally are designed, implemented, and supervised by statisticians whose expertise is in analytic design and data analysis. Their training and experience usually do not prepare them to guard against eITors related to biases in enrollment or unreliability of data. No matter how sophisti- cated the design of a study and no matter how skilled the analysis, unreliable data and selective enrollment of patients can undermine even a randomized trial. Trials designed in this fashion leave little or no room for the collection of data about health status. However, some studies do include health status mea- sures. How have these studies been designed and conducted? Answering this question requires one to recognize that health status is not the term ordinarily used when clinical investigators want to examine treatment effects that are not biomedical. Instead, quality of life is assessed. Now, is there a difference between health status and quality of life? MEASUREMENT OF QUALITY OF LIFE AND OF HEALTH STATUS Quality of life is not defined in the reports of clinical trials that I have read. The reader must deduce a definition from the dimensionsl that are assessed. A review of the literature shows that quality of life may include any one or a com- bination of the following factors: physical activity, social and leisure activity, work, symptoms, loss of income, cognition, emotional adaptation, self-esteem, lThe word dimension refers to an area of interest or concern that is measured by sev- eral interrelated variables. For example, cardiovascular function is a dimension of health measured by blood pressure, treadmill performance, EKG, etc.; mental status is a dimen- sion of health that may be measured by cognitive level, mood, effect, etc.

ADVANCES IN HEALTH STATUS MEASUREMENT TABLE 3.1 Suggested domains of quality of life 25 Symptoms Functional status Role activities Self care Mobility Physical activity Work Household management Social functioning Personal interactions . Intimacy Community interactions Emotional status Anxiety Stress Depression Locus of control Spiritual well-being Cognition Sleep and rest Energy and vitality Health perceptions General life satisfaction anxiety, stress, sexual activity, interpersonal relationships, impotence, inconti- nence, and overall satisfaction with life. Each investigation that purports to address quality of life actually examines a very narrow set of factors. Reasons for the choice of factors are rarely made clear, nor are the reasons for omitting elements that might be relevant. Table 3.1 provides a list of dimensions of quality of life that were suggested by conferees at a workshop on quality of life and cardiovascular disease. You should note the breadth of the dimensions covered and the fact that there is no suggestion of the interrelationship between dimensions. Conceptual frameworks for health status, on the other hand, have appeared in the literature, have been extensively discussed, and have provided the underpin- nings of several measures. One of these conceptualizations is given in Table 3.2. This table indicates the dimensions that constitute health status and how they relate to one another. It is clearly concerned with health, not with other aspects of life which may influence its quality. Systematic measures of functional status have been used by clinical researchers for more than 50 years. The first were developed to assess the base- line performance status of participants in clinical research projects. In some cases they were used to determine patient eligibility for participation in a trial. The Karnofsky Performance Status Index, the New York Heart Association Classification, and the Specific Activity Scale are examples. They have at least three distinguishing characteristics: they are brief, with patients assigned to one of no more than ten categories; each is specific to a particular disease or condi- tion; and they usually are completed by a physician on the basis of observation and history of the patient. All these measures of functional status were developed by physicians or other clinicians to systematize the collection and recording of information thought relevant for diagnosis and treatment; none was subjected to rigorous

26 TABLE 3.2 The dimensions of health status MARILYN BERGNER Genetic foundation Biologic, physiologic, anatomic condition Disease state Disability or handicapped state Functional condition Social role performance Physical performance Cognitive performance Mental condition Mood or feeling state Affective state Health potential Longevity Functioning Disease and disability Disadvantage Adapted from Bergner, M. Measurement of Health Status. Medical Care 1985;23:696 development and testing. Thus, their reliability tends to be poor, which pre- cludes their use for monitoring patient progress or assessing outcome of thera- py. This does not mean that they are not used for these purposes. In fact, they are probably the most commonly used measures of quality of life. However, none of them requires that the patients be asked directly about the characteris-

ADVANCES IN HEALTH STATUS MEASUREMENT 27 tics assessed, even though the recorder a doctor or nurse—may not have the information necessary to provide a reliable assessment. In sharp contrast with these measures is a group of measures, called health status measures, which have been developed relatively recently and have a gen- eral focus. All of them include physical functioning, but they also include other aspects of health, these may be symptoms, emotional status, cognition, or perceptions of health. The developers of health status measures expected their results to be valu- able for formulating health policy, since they provide information about the health status of populations and about the benefits of new therapies or systems of health services delivery, such as increased use of home health services. These purposes are distinct from those articulated by the developers of mea- sures for use in clinical practice. Because the group of measures aimed at clinical research was not intended for routine use in a physician's office, however, developers were not concerned with the amount of time it would add to a patient visit, whether the doctor, patient, nurse, or receptionist would complete it, or whether the number of questions was small enough to be tolerated by the staff. In fact, in most cases the aims were directly opposite to those encountered in developing a measure of health status for clinical practice. They were: · the need to be comprehensive, so that all aspects of health status were included; · the need to specify a method for answering the questions that did not involve clinicians; and · the need to assure reliable measurement (which often means longer mea- sures) because the research setting precludes assurance that a nurse or physi- cian will determine the reliability of a response. Many of these general health status measures have been carefully developed and are used extensively. They provide hard data that are reliable and repro- ducible. In fact, the data they produce are often more reliable than physiologic data. What physiologic test has a reliability coefficient of .90? Several health status measures do. A valuable discussion of the various general measures is provided in Measuring Health, by McDowell and Newell (11. Table 3.3, taken from this book, lists some general health status measures. In addition to these general health status measures, disease-specific mea- sures have been used in clinical research. The rationale for their development and use is that they address the specific concerns of the clinical entity being investigated, they can be shorter than the general measures, and they may be more sensitive to the changes that occur with treatment. All the new disease- specific measures have been developed with the same care as the general mea- sures. They do not ask for a clinician's judgment about the patient's condition, and they meet stringent reliability standards.

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ADVANCES IN HEALTH STATUS MEASUREMENT INCLUSION OF QUALITY OF LIFE AND HEALTH STATUS MEASURES IN CLINICAL TRIALS 29 Despite the availability of health status measures, quality of life measure- ment in clinical trials is often an afterthought. Clinical trials are designed to examine a medical outcome: tumor shrinkage, longevity, pulmonary function, renal function, level of angina, shortness of breath, and so on. But what hap- pens when, long after all aspects of the research have been settled, someone realizes that the therapy may affect aspects of a person's life that are not strictly medical. It may not be pleasant to become bald and nauseated, to eat a restrict- ed diet, or to be tied to a machine for 12 of 24 hours. Because such conse- quences of treatment and treatment-related side effects can affect all aspects of a patient's life, a quality of life assessment is deemed necessary. This assessment must meet certain criteria, however: it must fit into the planned data collection scheme; it must be short so as not to burden the patient; it must take no more than 15 minutes of the data collector's time; and it must be immediately acceptable and understandable to all the clinical members of the research team. These are formidable requirements which often preclude the use of well-developed health status measures. Furthermore, while the collection of biomedical data for clinical trials may require the skills of a clinician, health status data are particularly prone to biases that can be introduced by clinicians. The most obvious bias is the possibility that patients will not provide accurate information if they believe it will embarrass the clinician or reflect poorly on their own behavior. Nonetheless, drug companies and manufacturers of medical devices have become consumers of quality of life and health status assessments. At one time their interest in this area was confined to very specific side effects. That has changed over the past few years, for two reasons. One is the demand of third- party payers for more extensive evidence of the benefits of new drugs and devices, especially when they may be more costly. The other is the marketing advantage that may accrue if a new drug is shown to improve quality of life. Drug companies have undertaken a large number of quality of life and health status studies. Unfortunately, most of them are not published. In fact, only two have been, the captopril and auranofin trials (2,3), and I, for one, am tired of hearing about them as the harbingers of good things to come. What is interest- ing about these two studies, however, is their differences. The auranofin trial used well-developed multidimensional general measures that provide a health status score for each patient. The captopril study used a hodgepodge of inde- pendent measures to assess a variety of factors including distress, fatigue, impo- tence, and cognition. Some measures had already been developed, some were modifications of existing measures, and some were newly developed for the study. There was no way to combine the measures into a single index score. Most distressing to those of us in the field, the measures themselves are not available to other investigators. Though I am aware of several other drug and

30 MARILYN BERGNER device studies that have used health status measures, they have not been pub- lished and intonation about them is difficult if not impossible to obtain. I also know of studies that were never implemented or were sharply curtailed because manufacturers feared they would provide unfavorable evidence about products. After all, if the patient is asked about a series of symptoms or prob- lems or dysfunctions that may be interpreted as side effects, some may turn up. If, on the other hand, only the physician provides this information, it is usually filtered by selective questioning of the patient. Thus, no unexpected or unlikely effects good or bad generally are found. Aquired immune deficiency syndrome (AIDS) provides a perfect example of this. There was early evidence that AZT might have some deleterious side effects, but there was little interest in systematic examination of these effects. Only now that some work has been done by independent investigators does there seem to be interest by those directly involved in the development of new AIDS drugs in examining these effects. FOUR PROBLEMS REGARDING THE MEASUREMENT OF HEALTH STATUS IN CLINICAL TRIALS My review of clinical research that assesses health status identified four broad issues: conceptualization of a construct, the value of a gold standard, the clinical significance and sensitivity of the measures, and practical administra- tive problems. The major issue is conceptualization. The terms quality of life, health status, and functional status are often used interchangeably and without definition. Clinical investigators naively ask about a measure of quality of life, as if there were a single best exemplar to be used in all cases. Quality of life, like health or illness, must be assessed specifically. Although a few basic measurements (such as temperature; blood pressure; difficulty eating, sleeping, or dressing) may apply to everyone in every situation, many more are relevant only to par- ticular patients (such as glomerular filtration, ejection fraction, pain, impotence, walking, cognition). Each investigator must think about a study in terms of the intervention and patients involved, and decide what to assess. In general, the assessment should examine factors that are likely to be affected by the interven- tion, factors that may be affected, and factors that are unlikely to occur but are possible. Once the dimensions or categories are identified, appropriate mea- sures can be selected for use. Somewhere in the process of deciding on dimensions and choosing mea- sures, clinical investigators often start a futile search for the gold standard that everyone will find appropriate and credible. The bitter truth is that there is no gold standard, there is unlikely ever to be one, and it is unlikely that one is desirable. Health, like intelligence, is a complex attribute that requires a multi- dimensional measure. There is no gold standard for intelligence tests. Many are psychometrically sound and have been used enough to assure investigators

ADVANCES IN HEALTH STATUS MEASUREMENT 50 40 30 CL CO ~ 20 > 10 o o _ _ -Joann 8 <' ~ 0 ~ <r ° ~ ~ ~ ~ ° ~ <: ~ e ~ ~ x ~ x .O in 0 ~ 0 0 llJ O ~ POPUlATION 31 FIGURE 3.1 Overall Sickness Impact Profile (SIP) scores for different disease conditions or popu- lation groups. SOURCE: Patrick DL, Deyo RA. Generic and disease-specific measures in assess- ing health status and quality of life. In: Advances in Health Status Assessment: Conference Proceedings. Medical Care 1989;27(3):S220. that they "work." The choice of a test depends on the particular situation. However, intelligence tests do have an important advantage over measures of health status. They have been used enough that the meaning of a score is under- stood, and a difference of three or five or ten points can be translated, however crudely, into a mental picture of what the person can do. When individuals dif- fer, there is confidence that the test will pick up the difference. The clinical importance of score differences and health status is still unclear, and the meaning of any particular score on a health status measure produces no mental pictures that represents real people or real patients. However, a recently published article may soon remedy this situation a bit (4~. Patrick and Deyo have reviewed many studies that used the Sickness Impact Profile, one of the more commonly applied general health status measures, and put together Figure 3.1. The administrative problems that I have alluded to are not easily solved. They are principally concerned with determination of health status for those

32 MARILYN BERGNER persons for whom current measures may be inappropnate. These include the emotionally or cognitively impaired, the illiterate, those not proficient in English, and those not familiar with American culture. These problems are inherent in obtaining any data that require communication with a patient, not only health status measures. The advantage of health status measures is that we know how they should behave if they are used properly. If investigators use measures that are well developed, they may become convinced that they need not develop something new for each malt That step alone would increase the efficiency of clinical ~i- als. It would also begin to develop a body of experience that could advance the acceptance of such measures by regulatory agencies. With such acceptance may come a greater appreciation of the importance of health-related quality of life as a major goal of technology development. REFERENCES McDowell I, Newell C. Measuring Health: A Guide to Rating Scales and Questionnaires. New York: Oxford University Press, 1987:270. 2. Croog SH, Levine S. Testa MA, Brown B. Elulpitt CJ, Jenkins CD, Klerman GL, Williams GH. The effects of antihypertensive therapy on the quality of life. New England Journal of Medicine 1986;314:1657-1664. 3. Bombardier C, Ware J. Russell IJ, Larson M, Chalmers A, Read JL. Auranofin therapy and quality of life in patients with rheumatoid arthritis: Results of a multi- center trial. American Journal of Medicine 1986;81:565-578. 4. Patrick DL, Deyo, RA. Generic and disease-specific measures in assessing health status and quality of life. In: Lohr KN (ed.) Advances in Health Status Assessment: C o n f e r e n c e P r o c e e d i n g s . 1 9 8 9 ; 2 7 : S 2 1 7 - S 2 3 2 .

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The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them.

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